Application of Genetic Algorithm into Multicriteria Batch Manufacturing Scheduling

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Izvoz citacije: ABNT
SLAK, Aleš ;TAVČAR, Jože ;DUHOVNIK, Jože .
Application of Genetic Algorithm into Multicriteria Batch Manufacturing Scheduling. 
Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 57, n.2, p. 110-124, june 2018. 
ISSN 0039-2480.
Available at: <https://www.sv-jme.eu/sl/article/application-of-genetic-algorithm-into-multicriteria-batch-manufacturing-scheduling/>. Date accessed: 22 nov. 2019. 
doi:http://dx.doi.org/10.5545/sv-jme.2010.122.
Slak, A., Tavčar, J., & Duhovnik, J.
(2011).
Application of Genetic Algorithm into Multicriteria Batch Manufacturing Scheduling.
Strojniški vestnik - Journal of Mechanical Engineering, 57(2), 110-124.
doi:http://dx.doi.org/10.5545/sv-jme.2010.122
@article{sv-jmesv-jme.2010.122,
	author = {Aleš  Slak and Jože  Tavčar and Jože  Duhovnik},
	title = {Application of Genetic Algorithm into Multicriteria Batch Manufacturing Scheduling},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {57},
	number = {2},
	year = {2011},
	keywords = {genetic algorithm; multicriteria scheduling; batch production; target function},
	abstract = {Technical innovations in the area of manufacturing logistics are introduced partially and thus fail to realize their full potential. In order to optimise the efficiency of turning manufacturing processes, the production planning and scheduling, cutting tools and material flow process, manufacturing capacities have been analysed. All data from production operations, quantities and the, duration of operations are now kept in the ERP system. It provided the necessary condition for the establishment of a robust planning model, which includes stock control of material and cutting tools. An update was required for the whole lifecycle of products and means of work. The article presents information and an algorithm for a dynamic scheduling model, based on a genetic algorithm. The orders on the machines are scheduled on the basis of a genetic algorithm, according to the target function criteria. The algorithm provides a satisfactory, almost ideal solution, which is good enough for implementation in practice. With the GA the machine utilization increased, throughput time was reduced and costs and delivery delays improved. The presented model of GA also allows further optimisation of manufacturing plans and the machines layout.},
	issn = {0039-2480},	pages = {110-124},	doi = {10.5545/sv-jme.2010.122},
	url = {https://www.sv-jme.eu/sl/article/application-of-genetic-algorithm-into-multicriteria-batch-manufacturing-scheduling/}
}
Slak, A.,Tavčar, J.,Duhovnik, J.
2011 June 57. Application of Genetic Algorithm into Multicriteria Batch Manufacturing Scheduling. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 57:2
%A Slak, Aleš 
%A Tavčar, Jože 
%A Duhovnik, Jože 
%D 2011
%T Application of Genetic Algorithm into Multicriteria Batch Manufacturing Scheduling
%B 2011
%9 genetic algorithm; multicriteria scheduling; batch production; target function
%! Application of Genetic Algorithm into Multicriteria Batch Manufacturing Scheduling
%K genetic algorithm; multicriteria scheduling; batch production; target function
%X Technical innovations in the area of manufacturing logistics are introduced partially and thus fail to realize their full potential. In order to optimise the efficiency of turning manufacturing processes, the production planning and scheduling, cutting tools and material flow process, manufacturing capacities have been analysed. All data from production operations, quantities and the, duration of operations are now kept in the ERP system. It provided the necessary condition for the establishment of a robust planning model, which includes stock control of material and cutting tools. An update was required for the whole lifecycle of products and means of work. The article presents information and an algorithm for a dynamic scheduling model, based on a genetic algorithm. The orders on the machines are scheduled on the basis of a genetic algorithm, according to the target function criteria. The algorithm provides a satisfactory, almost ideal solution, which is good enough for implementation in practice. With the GA the machine utilization increased, throughput time was reduced and costs and delivery delays improved. The presented model of GA also allows further optimisation of manufacturing plans and the machines layout.
%U https://www.sv-jme.eu/sl/article/application-of-genetic-algorithm-into-multicriteria-batch-manufacturing-scheduling/
%0 Journal Article
%R 10.5545/sv-jme.2010.122
%& 110
%P 15
%J Strojniški vestnik - Journal of Mechanical Engineering
%V 57
%N 2
%@ 0039-2480
%8 2018-06-28
%7 2018-06-28
Slak, Aleš, Jože  Tavčar, & Jože  Duhovnik.
"Application of Genetic Algorithm into Multicriteria Batch Manufacturing Scheduling." Strojniški vestnik - Journal of Mechanical Engineering [Online], 57.2 (2011): 110-124. Web.  22 Nov. 2019
TY  - JOUR
AU  - Slak, Aleš 
AU  - Tavčar, Jože 
AU  - Duhovnik, Jože 
PY  - 2011
TI  - Application of Genetic Algorithm into Multicriteria Batch Manufacturing Scheduling
JF  - Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2010.122
KW  - genetic algorithm; multicriteria scheduling; batch production; target function
N2  - Technical innovations in the area of manufacturing logistics are introduced partially and thus fail to realize their full potential. In order to optimise the efficiency of turning manufacturing processes, the production planning and scheduling, cutting tools and material flow process, manufacturing capacities have been analysed. All data from production operations, quantities and the, duration of operations are now kept in the ERP system. It provided the necessary condition for the establishment of a robust planning model, which includes stock control of material and cutting tools. An update was required for the whole lifecycle of products and means of work. The article presents information and an algorithm for a dynamic scheduling model, based on a genetic algorithm. The orders on the machines are scheduled on the basis of a genetic algorithm, according to the target function criteria. The algorithm provides a satisfactory, almost ideal solution, which is good enough for implementation in practice. With the GA the machine utilization increased, throughput time was reduced and costs and delivery delays improved. The presented model of GA also allows further optimisation of manufacturing plans and the machines layout.
UR  - https://www.sv-jme.eu/sl/article/application-of-genetic-algorithm-into-multicriteria-batch-manufacturing-scheduling/
@article{{sv-jme}{sv-jme.2010.122},
	author = {Slak, A., Tavčar, J., Duhovnik, J.},
	title = {Application of Genetic Algorithm into Multicriteria Batch Manufacturing Scheduling},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {57},
	number = {2},
	year = {2011},
	doi = {10.5545/sv-jme.2010.122},
	url = {https://www.sv-jme.eu/sl/article/application-of-genetic-algorithm-into-multicriteria-batch-manufacturing-scheduling/}
}
TY  - JOUR
AU  - Slak, Aleš 
AU  - Tavčar, Jože 
AU  - Duhovnik, Jože 
PY  - 2018/06/28
TI  - Application of Genetic Algorithm into Multicriteria Batch Manufacturing Scheduling
JF  - Strojniški vestnik - Journal of Mechanical Engineering; Vol 57, No 2 (2011): Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2010.122
KW  - genetic algorithm, multicriteria scheduling, batch production, target function
N2  - Technical innovations in the area of manufacturing logistics are introduced partially and thus fail to realize their full potential. In order to optimise the efficiency of turning manufacturing processes, the production planning and scheduling, cutting tools and material flow process, manufacturing capacities have been analysed. All data from production operations, quantities and the, duration of operations are now kept in the ERP system. It provided the necessary condition for the establishment of a robust planning model, which includes stock control of material and cutting tools. An update was required for the whole lifecycle of products and means of work. The article presents information and an algorithm for a dynamic scheduling model, based on a genetic algorithm. The orders on the machines are scheduled on the basis of a genetic algorithm, according to the target function criteria. The algorithm provides a satisfactory, almost ideal solution, which is good enough for implementation in practice. With the GA the machine utilization increased, throughput time was reduced and costs and delivery delays improved. The presented model of GA also allows further optimisation of manufacturing plans and the machines layout.
UR  - https://www.sv-jme.eu/sl/article/application-of-genetic-algorithm-into-multicriteria-batch-manufacturing-scheduling/
Slak, Aleš, Tavčar, Jože, AND Duhovnik, Jože.
"Application of Genetic Algorithm into Multicriteria Batch Manufacturing Scheduling" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 57 Number 2 (28 June 2018)

Avtorji

Inštitucije

  • Iskra ISD-Strugarstvo d.o.o., 110 Savska loka 4, SI-4000 Kranj 1
  • Iskra Mehanizmi 2
  • University of Ljubljana, Faculty of Mechanical Engineering 3

Informacije o papirju

Strojniški vestnik - Journal of Mechanical Engineering 57(2011)2, 110-124

https://doi.org/10.5545/sv-jme.2010.122

Technical innovations in the area of manufacturing logistics are introduced partially and thus fail to realize their full potential. In order to optimise the efficiency of turning manufacturing processes, the production planning and scheduling, cutting tools and material flow process, manufacturing capacities have been analysed. All data from production operations, quantities and the, duration of operations are now kept in the ERP system. It provided the necessary condition for the establishment of a robust planning model, which includes stock control of material and cutting tools. An update was required for the whole lifecycle of products and means of work. The article presents information and an algorithm for a dynamic scheduling model, based on a genetic algorithm. The orders on the machines are scheduled on the basis of a genetic algorithm, according to the target function criteria. The algorithm provides a satisfactory, almost ideal solution, which is good enough for implementation in practice. With the GA the machine utilization increased, throughput time was reduced and costs and delivery delays improved. The presented model of GA also allows further optimisation of manufacturing plans and the machines layout.

genetic algorithm; multicriteria scheduling; batch production; target function